Here is the most efficient way I have found to rename multiple columns using a combination of purrr::set_names() and a few stringr operations.
library(tidyverse)
# Make a tibble with bad names
data <- tibble(
`Bad NameS 1` = letters[1:10],
`bAd NameS 2` = rnorm(10)
)
data
# A tibble: 10 x 2
`Bad NameS 1` `bAd NameS 2`
<chr> <dbl>
1 a -0.840
2 b -1.56
3 c -0.625
4 d 0.506
5 e -1.52
6 f -0.212
7 g -1.50
8 h -1.53
9 i 0.420
10 j 0.957
# Use purrr::set_names() with annonymous function of stringr operations
data %>%
set_names(~ str_to_lower(.) %>%
str_replace_all(" ", "_") %>%
str_replace_all("bad", "good"))
# A tibble: 10 x 2
good_names_1 good_names_2
<chr> <dbl>
1 a -0.840
2 b -1.56
3 c -0.625
4 d 0.506
5 e -1.52
6 f -0.212
7 g -1.50
8 h -1.53
9 i 0.420
10 j 0.957